Symbolic representation and retrieval of moving object trajectories

  • Authors:
  • Lei Chen;M. Tamer Özsu;Vincent Oria

  • Affiliations:
  • University of Waterloo, Waterloo, Canada;University of Waterloo, Waterloo, Canada;New Jersey Inst. of Technology, Newark, NJ

  • Venue:
  • Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
  • Year:
  • 2004

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Abstract

Searching moving object trajectories of video databases has been applied to many fields, such as video data analysis, content-based video retrieval, video scene classification. In this paper, we propose a novel representation of trajectories, called movement pattern strings, which convert the trajectories into symbolic representations. Movement pattern strings encode both the movement direction and the movement distance information of the trajectories. The distances that are computed in a symbolic space are lower bounds of the distances of original trajectory data, which guarantees that no false dismissals will be introduced using movement pattern strings to retrieve trajectories. In order to improve the retrieval efficiency, we define a modified frequency distance for frequency vectors that are obtained from movement pattern strings to reduce the dimensionality and the computation cost. The experimental results show that using movement pattern strings is almost as effective as using raw trajectories. In addition, the cost of retrieving similar trajectories can greatly be reduced when the modified frequency distance is used as a filter